[unreadable] The main objective of this grant is to facilitate X-ray interventional procedures by developing an imaging platform that provides exact cone beam reconstruction of anatomical images and immediate volume-tomographic information on contrast dynamics to assess the functional effects of interventions. We have recently developed an extension of the CT Central Slice Theorem to directly provide the Fourier transform of the imaged volume using acquired cone beam data. This will be combined with a paired orthogonal-arc acquisition on a recently introduced flat-panel detector C-arm system to provide improved 3D anatomical images. For dynamic contrast studies, time resolved data will be acquired using simultaneous orthogonal rotation, resulting in an elliptical tomographic data set that will provide contrast dynamical information in planes generated by a novel tomosynthetic algorithm that exploits the divergent beam k-space formalism. In the R121 phase, computer simulations will be performed to optimize and demonstrate the feasibility of the proposed tomosynthetic reconstruction techniques and contrast dynamics analysis. In the FY33 phase, acquisition of volume data using a novel CC-geometry will be implemented and subjected to optimized cone-beam reconstruction algorithms to provide improved anatomical images. Two orthogonal simultaneous linear motions of an intelventioanal LC-arm system will be synchronized to prototype elliptical tomographic acquisition. The performance characteristics of this system will be investigated and optimized. The combined anatomical and time-resolved tomosynthetic capabilities will be integrated into a single C-arm unit. Finally, an animal perfusion model will be used to validate the contrast dynamic capabilities of the system. [unreadable] The proposed interventional system should find application in the evaluation of interventions following stroke and could facilitate and optimize the treatment of tumors, where perfusion endpoints could be useful in guiding embolization of meningiomas, hepatic cancers, or uterine fibroid tumors. [unreadable] [unreadable]